A Blast From the Past: Personalizing Predictions of Video-Induced Emotions using Personal Memories as Context
Bernd Dudzik, Joost Broekens, Mark Neerincx, Hayley Hung
A key challenge in the accurate prediction of viewers' emotional responses to
video stimuli in real-world applications is accounting for person- and
situation-specific variation. An important contextual influence shaping
individuals' subjective experience of a video is the personal memories that it
triggers in them. Prior research has found that this memory influence explains
more variation in video-induced emotions than other contextual variables
commonly used for personalizing predictions, such as viewers' demographics or
personality. In this article, we show that (1) automatic analysis of text
describing their video-triggered memories can account for variation in viewers'
emotional responses, and (2) that combining such an analysis with that of a
video's audiovisual content enhances the accuracy of automatic predictions. We
discuss the relevance of these findings for improving on state of the art
approaches to automated affective video analysis in personalized contexts.